1. Function Implementations
1.1 function 1: ReadFile and attach packages
1.2. function 2: Wave
1.3. function 3: fourier_smooth
1.4. function 4: fPCA.nodes
1.5. function 5: node.scaler
1.6. function 6: row.check
1.7 function pc.df
it’s to put variance on Principle Components into dataframe
main script
1. Parkinson Disease - Placebo Group
pd_placebo <- c(1,4,6,10,14,15,18,20,22,23,31,46,47,50,56,60,61,64,65,80,81,91,97)
for (i in pd_placebo){
df_name <- paste("patient", i, sep = "")
assign(df_name, ReadFile(paste('/Users/hanwang/desktop/Git_desktop/Functional_Data_Analysis/Data for Zach/Data for Zach ', i,'.csv', sep=""),
time_subset=c(1:600), node_subset=c(1:32)))
tmp=pc.df(ReadFile(paste('/Users/hanwang/desktop/Git_desktop/Functional_Data_Analysis/Data for Zach/Data for Zach ', i,'.csv', sep=""),
time_subset=c(1:600), node_subset=c(1:32)))
a =tmp$pc1
a$index = c(1:80)
d <- melt(data = a, id.vars = c("index"), measure.vars = colnames(patient1))
print(ggplot(d, aes(x = index, y = value)) +
geom_line(aes(color = variable)))+ggtitle(paste("patient", i))
}




















